Analysis of cost model with queuing system under uncertainty

Kordasiabi, Maedeh Chaleshigar; Gholizadeh, Hadi; Fazlollahtabar, Hamed; Javadian, Nikbakhsh

doi:10.1080/21681015.2020.1797911

Cited by 6 publications

(3 citation statements)

References 29 publications

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“…Sallam and Zobu [22] using simulation data on a queuing model with sequential two stations (stages) and all other conditions well defined, concluded that the simulation results approximated the theoretical results. So many authors have used queuing models in one way or the other among whom are Qureshi et al [21], Srinivas et al [25], Famule [8], Keaogile et al [13] ,Gumus et al [10], Kembe et al [14], Aradhye and Kallurkar [4], Cho et al [6] , Maedeh et al [15], Adan [1], Conte et al [7], Ugwuishiwu et al [27] ,Afrane and Appah [2] , Kama and Mankilik [12], Mukherjee and Whalen [16], Jo et al [11].…”

Section: Literaturementioning

confidence: 99%

Waiting Time Before Justice in the Law Sector: A QUEUEING Theory

Oghenekevwe¹,

Peace²,

Abidemi³

et al. 2021

AJTAS

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The legal system in Nigeria is be-deviled with delayed justice which has become a source of concern to many person. This is very much peculiar to those who feel that the judiciary is too slow in resolving legal issues in Nigeria. In Nigeria, there abound court cases especially those of criminal dimensions that have ongoing for years now without reaching a conclusive conclusion. The study is aimed at modelling the queuing system in the magistrate courts in Onitsha Magisterial districts. The specific objectives include: to apply the M/M/2 and M/M/3 models with identical and parallel queues to criminal cases in the Magistrate court and to compare the efficiency of the two models and in either cases to determine time to justice in criminal cases in the Magisterial District. The results of the study show that M/M/2 model with 2 identical and parallel queues have an expected number of cases in the system as 39 with 50% idle time while the M/M/3 model with 3 identical and parallel queues have an expected number of cases in the system as 23 cases with 64.88% idle time. The comparison of the two models shows M/M/2 with 2-identical and parallel queues is more efficient as it has more number of cases to attend to and less idle time. The study therefore concludes that the delays in the disposal of cases especially those with criminal nature may not be attributable to the queuing systems in place. Even though lesser number of servers is seen to be efficient, this may not be advised. Increasing the number of servers though will increase speed of disposal of cases, may also lead to increased idle time of servers. As more courts being set up may result in waste of resources, manpower and time as the 2-server system is efficient in speeding up justice delivery in the magisterial division.

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Section: Literaturementioning

confidence: 99%

Waiting Time Before Justice in the Law Sector: A QUEUEING Theory

Oghenekevwe¹,

Peace²,

Abidemi³

et al. 2021

AJTAS

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“…Customers are drawn to the company as a result of these promotions (known as encouraged arrivals, a term coined by [1]), but if businesses do not prepare themselves to run efficiently during the promotion period to give customers an amazing service experience, their reputation may suffer.Therefore, companies must be aware of their performance level in advance to manage service quality and reduce customer wait times. Although discounts and offers tempt customers to wait longer, they have greater patience (referred [2] & [3]), decreasing the likelihood that they will abandon the system. Customers are drawn to the business in [6] by Haight by the perception of a sizable base.…”

Section: Introductionmentioning

confidence: 99%

“…Customers are drawn to the business in [6] by Haight by the perception of a sizable base. Reverse balking, on the other hand, deals with the likelihood of joining or not joining the system, whereas engaged customers join because they are aware that the organisation will continue to offer them discounts and benefits, analysis by "Haid" [3] in which the steady state solution is carried out in a solitary queuing model. By analyzing the rate of balking and reneging in 1957 and 1963, Haight and Gafarain [5], [7] & [8] provide some insight.…”

Section: Introductionmentioning

confidence: 99%

Economical Situation of the M/M/1/κ Markovian Queueing system with Encouraged Incoming and maintained of Reneged Customers

A.Sridhar

2023

tjjpt

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Today’s businesses all strive to operate smoothly and efficiently in order to meet customer demandand provide the best possible service because of the intense competition. The queuing theory is crucial in this situation. Queueing models can assist businesses in understanding their performance in advance, enabling themto plan effectively for providing seamless and effective customer service as well as long-term sustainability. Businesses entice customers to sign up for the system by offering promotions and discounts. Customers wait even longer in queue to receive services as a result of incentives like discounts.An analysis is conducted on a finite Markovian single-server queuing model with encouraged arrivals, reneging, and retention of reneged customers. Iterative derivation is used to reach the model's steady state solution. Additionally, the queueing model's performance metrics are gathered. As unique example of this model,several significant queuing models are derived. In order to develop a cost model, a model's economic analysis is presented, and a discussion of numerical representation is also included.Customers are added when they are welcomed, which changes the way theybehave in a queueing system.

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Joint replacement and production control for a queueing system with different failures

Wang

2021

Journal of Industrial and Production Engineering

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Analysis of cost model with queuing system under uncertainty

Cited by 6 publications

References 29 publications

Waiting Time Before Justice in the Law Sector: A QUEUEING Theory

Waiting Time Before Justice in the Law Sector: A QUEUEING Theory

Economical Situation of the M/M/1/κ Markovian Queueing system with Encouraged Incoming and maintained of Reneged Customers

Joint replacement and production control for a queueing system with different failures

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